In this study, the authors present an overview of closed‐loop subspace identification
methods found in the recent literature. Since a significant number of algorithms has …

Mathematical models of dynamic systems are required in most areas of scientific enquiry
and take various forms, such as differential equations, difference equations, state-space …

This paper deals with equation error methods that fit continuous-time transfer function
models to discrete-time data recently included in the CONTSID (CONtinuous-Time System …

The problem of identification of linear continuous-time (CT) state–space (SS) models directly
from time-domain data is considered. Given multi-sine waves as excitation signals, this …

Accurate dynamic modeling of helicopter aeromechanics is becoming increasingly
important, as progressively stringent requirements are being imposed on rotorcraft control …

This paper presents a novel approach for system identification of continuous-time stochastic
state space models from random input–output continuous data. The approach is based on …

When identifying a continuous-time AR process from discrete-time data, an obvious
approach is to replace the derivative operator in the continuous-time model by an …

This paper presents a methodology for system identification of continuous-time state-space
models from finite sampled input-output signals. The estimation problem of the consecutive …

In this paper a new deterministic subspace approach is introduced for multi-dimensional
nonlinear system identification based on output-only measurements. The strategy is to excite …

We develop a simple relay feedback method to identify Wiener-type nonlinear processes. It
separates the identification problem of the nonlinear static function from that of the linear …